Award Date
5-1-2019
Degree Type
Thesis
Degree Name
Master of Science in Computer Science
Department
Computer Science
First Committee Member
Wolfgang Bein
Second Committee Member
Ajoy Datta
Third Committee Member
Laxmi Gewali
Fourth Committee Member
Henry Selvaraj
Number of Pages
67
Abstract
A large number of real-world planning problems are combinatorial optimization problems which are easy to state and have a finite but usually very large number of feasible solutions. The minimum spanning tree problem and the shortest path problem are some which are solvable through polynomial algorithms. Even though there are other problems such as crew scheduling, vehicle routing, production planning, and hotel room operations which have no properties such as to solve the problem with polynomial algorithms. All these problems are NP-hard. The permutation flow shop problem is also NP-hard problem and they require high computation. These problems are solvable as in the form of the optimal and near-optimal solution. Some approach to get optimal are exhaustive search and branch and bound whereas near optimal are achieved annealing, Genetic algorithm, and other various methods.
We here have used different approach exhaustive search, branch and bound and genetic algorithm. We optimize these algorithms to get performance in time as well as get the result closer to optimal. The exhaustive search and branch and bound gives all possible optimal solutions. We here have shown the comparative result of optimal calculation for 10 jobs with varying machine number up to 20. The genetic algorithm scales up and gives results to the instances with a larger number of jobs and machines.
Keywords
Branch and bound; Exhaustive search; Genetic algorithm; Multi-threading; Permitation flowshop; VFR instances
Disciplines
Computer Sciences
File Format
Degree Grantor
University of Nevada, Las Vegas
Language
English
Repository Citation
Sapkota, Hari Prasad, "Benchmarking Permutation Flow Shop Problem: Adaptive and Enumerative Approaches Implementations via Novel Threading Techniques" (2019). UNLV Theses, Dissertations, Professional Papers, and Capstones. 3668.
http://dx.doi.org/10.34917/15778531
Rights
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